Abstract:
In this thesis, we present two new methods for the design of microstrip filters based
on artificial intelligence techniques. After a theoretical study on functions of filtering
,microstrip structure and the technical design of microstrip filters, we applied the genetic
algorithm and particle swarm optimization to the design of two types of microstrip filters : a
lowpass filter with stepped impedance and a bandpass filtre with resonators coupled in
parallel. The lowpass filter designed by the two procedures developed is more efficient than
the Butterworth filter. The bandpass filter designed by our procedures is validated by the
literature scientific. Both methods are effective for the design of microstrip filters.
